Decoding Regression: Why Fewer Features Deliver Better Predictions

In an era of big data, feature correlation often leads to unstable models and overfitting. Principal Component Regression (PCR) and Partial Least Squares (PLS) provide essential frameworks for compressing complex data into stable, high-performance predictive components.